activity
20182025
most citedSemMT: A Semantic-based Testing Approach for Machine Translation Systems

41 citations · 108 across the 9 of their papers we have counts for

collaborators

9 papers

cs.SE2025

Vulnerability-Affected Versions Identification: How Far Are We?

Xingchu Chen, Chengwei Liu, Jialun Cao +6

Identifying which software versions are affected by a vulnerability is critical for patching, risk mitigation. Despite a growing body of tools, their real-world effectiveness remai…

cs.SD2023★ 1 cited

ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers

Yi Liu, Yuekang Li, Gelei Deng +7

The popularity of automatic speech recognition (ASR) systems nowadays leads to an increasing need for improving their accessibility. Handling stuttering speech is an important feat…

cs.CR2023★ 36 cited

How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation

Cen Zhang, Yaowen Zheng, Mingqiang Bai +6

LLM-based (Large Language Model) fuzz driver generation is a promising research area. Unlike traditional program analysis-based method, this text-based approach is more general and…

cs.SE2023★ 27 cited

ACETest: Automated Constraint Extraction for Testing Deep Learning Operators

Jingyi Shi, Yang Xiao, Yuekang Li +6

Deep learning (DL) applications are prevalent nowadays as they can help with multiple tasks. DL libraries are essential for building DL applications. Furthermore, DL operators are…

cs.PL2020★ 1 cited

TransRegex: Multi-modal Regular Expression Synthesis by Generate-and-Repair

Yeting Li, Shuaimin Li, Zhiwu Xu +5

Since regular expressions (abbrev. regexes) are difficult to understand and compose, automatically generating regexes has been an important research problem. This paper introduces…

cs.SE2020★ 41 cited

SemMT: A Semantic-based Testing Approach for Machine Translation Systems

Jialun Cao, Meiziniu Li, Yeting Li +2

Machine translation has wide applications in daily life. In mission-critical applications such as translating official documents, incorrect translation can have unpleasant or somet…

cs.DB2019★ 1 cited

An Effective Algorithm for Learning Single Occurrence Regular Expressions with Interleaving

Yeting Li, Haiming Chen, Xiaolan Zhang +1

The advantages offered by the presence of a schema are numerous. However, many XML documents in practice are not accompanied by a (valid) schema, making schema inference an attract…

cs.DB2019

Learning Restricted Regular Expressions with Interleaving

Chunmei Dong, Yeting Li, Haiming Chen

The advantages for the presence of an XML schema for XML documents are numerous. However, many XML documents in practice are not accompanied by a schema or by a valid schema. Relax…

cs.DB2018★ 1 cited

Practical Study of Deterministic Regular Expressions from Large-scale XML and Schema Data

Yeting Li, Xinyu Chu, Xiaoying Mou +2

Regular expressions are a fundamental concept in computer science and widely used in various applications. In this paper we focused on deterministic regular expressions (DREs). Con…